Introduction and datasets

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INTRO

For my corpus, I will use two of the playlists that spotify made for me. The first playlist is “Jouw topnummers van 2020” and the second playlist is “Jouw topnummers van 2021”. What I find interesting about these playlists is that they are in some way representative of the music that I listened to in 2020 and 2021. I’m interested in seeing if there are specific things that have changed when it comes to my music taste. I think the tracks in these playlists are quite representative when it comes to the music that I listened to during those periods of time.

When comparing two tracks, it seemed most logical to me to compare the number one songs from both years. For 2020 that song is : Why Why Why Why Why - Sault For 2021 that song is: I know you, I live you - Chaka Khan

Typical and Atypical tracks

Some typical tracks from the 2020 playlist:

Why Why Why Why Why - Sault

Colors - Black Pumas

Exit music (for a film) - Radiohead

Blue World - Mac Miller

H.f.g.w (Canyons Drunken Rage) - Tame Impala

Some atypical tracks from the 2020 playlist:

Fam - sor

Daisy - Ashnikko

Fragments of stasimon of Orestes by Euripides - Petros Tabouris

Some typical tracks from the 2021 playlist:

I know you, I live you - Chaka Khan

You Don’t Listen - General Elektriks

Famous - The Internet

Blackstar - David Bowie

Exit music (for a film) - Radiohead

Some atypical tracks from the 2021 playlist:

Temporary - Lauren Jauregui

SHUM - Go_A

Symphony No.5: IV. Adagietto. Sehr Langsam - Gustav Mahler

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Chart 1

# A tibble: 100 × 61
   playlist_id  playlist_name  playlist_img    playlist_owner_… playlist_owner_…
   <chr>        <chr>          <chr>           <chr>            <chr>           
 1 37i9dQZF1EL… Your Top Song… https://lineup… Spotify          spotify         
 2 37i9dQZF1EL… Your Top Song… https://lineup… Spotify          spotify         
 3 37i9dQZF1EL… Your Top Song… https://lineup… Spotify          spotify         
 4 37i9dQZF1EL… Your Top Song… https://lineup… Spotify          spotify         
 5 37i9dQZF1EL… Your Top Song… https://lineup… Spotify          spotify         
 6 37i9dQZF1EL… Your Top Song… https://lineup… Spotify          spotify         
 7 37i9dQZF1EL… Your Top Song… https://lineup… Spotify          spotify         
 8 37i9dQZF1EL… Your Top Song… https://lineup… Spotify          spotify         
 9 37i9dQZF1EL… Your Top Song… https://lineup… Spotify          spotify         
10 37i9dQZF1EL… Your Top Song… https://lineup… Spotify          spotify         
# … with 90 more rows, and 56 more variables: danceability <dbl>, energy <dbl>,
#   key <int>, loudness <dbl>, mode <int>, speechiness <dbl>,
#   acousticness <dbl>, instrumentalness <dbl>, liveness <dbl>, valence <dbl>,
#   tempo <dbl>, track.id <chr>, analysis_url <chr>, time_signature <int>,
#   added_at <chr>, is_local <lgl>, primary_color <lgl>, added_by.href <chr>,
#   added_by.id <chr>, added_by.type <chr>, added_by.uri <chr>,
#   added_by.external_urls.spotify <chr>, track.artists <list>, …

Chart 2

# A tibble: 100 × 61
   playlist_id  playlist_name playlist_img     playlist_owner_… playlist_owner_…
   <chr>        <chr>         <chr>            <chr>            <chr>           
 1 4uti3gC6MRx… JTNV2021      https://mosaic.… Noortje van der… noortjeenolaf   
 2 4uti3gC6MRx… JTNV2021      https://mosaic.… Noortje van der… noortjeenolaf   
 3 4uti3gC6MRx… JTNV2021      https://mosaic.… Noortje van der… noortjeenolaf   
 4 4uti3gC6MRx… JTNV2021      https://mosaic.… Noortje van der… noortjeenolaf   
 5 4uti3gC6MRx… JTNV2021      https://mosaic.… Noortje van der… noortjeenolaf   
 6 4uti3gC6MRx… JTNV2021      https://mosaic.… Noortje van der… noortjeenolaf   
 7 4uti3gC6MRx… JTNV2021      https://mosaic.… Noortje van der… noortjeenolaf   
 8 4uti3gC6MRx… JTNV2021      https://mosaic.… Noortje van der… noortjeenolaf   
 9 4uti3gC6MRx… JTNV2021      https://mosaic.… Noortje van der… noortjeenolaf   
10 4uti3gC6MRx… JTNV2021      https://mosaic.… Noortje van der… noortjeenolaf   
# … with 90 more rows, and 56 more variables: danceability <dbl>, energy <dbl>,
#   key <int>, loudness <dbl>, mode <int>, speechiness <dbl>,
#   acousticness <dbl>, instrumentalness <dbl>, liveness <dbl>, valence <dbl>,
#   tempo <dbl>, track.id <chr>, analysis_url <chr>, time_signature <int>,
#   added_at <chr>, is_local <lgl>, primary_color <lgl>, added_by.href <chr>,
#   added_by.id <chr>, added_by.type <chr>, added_by.uri <chr>,
#   added_by.external_urls.spotify <chr>, track.artists <list>, …

Energy

Column

Summary


2020:
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
 0.0440  0.4387  0.5535  0.5581  0.6700  0.9310 

2021:
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
0.00639 0.44575 0.58200 0.57077 0.71400 0.97600 

In the histogram, you can see the energy count per playlist. The included summary shows that both the median and the mean are not too far apart when you compare the 2020 and 2021 playlists. There is however, some difference when you look at the minimum and maximum energy. In my opinion this would mean that in 2021 I listened to a wider variety of music when it comes to energy.

The second chart shows that the 2020 playlist has a wider density. This could be explained by the minimum and maximum being less far apart, which makes the density wider.

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Energy Count

Energy per year 2

Energy-Valence

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Correlation 2020 - Energy / Valence
[1] 0.455756

Correlation 2021 - Energy / Valence
[1] 0.2139411

Energy valence

The first graph shows the relation between energy and valence for both 2020 and 2021. I also calculated the correlation between these two variables. That calculation suggests that there is more correlation between energy and valence in the 2020 playlist than in the 2021 playlist. This is visually confirmed by the second chart, which in addition to energy and valence, also shows minor and major. The values seem to be more scattered in the 2021 graph.

Something I found interesting about this graph is that in the 2020 chart, minor songs generally score higher than major songs when it comes to energy. Something I think could explain this is that the top ten songs with the highest energy are all (hard)rock songs. These songs are often quite high in energy, even when they are in a minor key.

Another thing I found interesting about this graph is that the song with both the least energy and valence in the 2021 chart, is actually a song that does not really belong in the playlist. Last year I took a Musicological History course, for which we had to take a listening test, to prove that we were able to recognize a song by hearing it. One of the songs that I struggled with while studying was Symphony No. 5: IV. Adagietto. Sehr langsam by Gustav Mahler. This is the song with the lowest energy and valence. This means that it is not really a representative song, since I didn’t listen to it because I wanted to, but because I had to.

Column

Energy Valence

Energy Valence Mode 4

Danceability

Column 1


2020
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
 0.2930  0.5745  0.6835  0.6737  0.7833  0.9460 

2021
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
 0.0618  0.5102  0.6410  0.6224  0.7455  0.9490 

Text explaining the data etc.

Column 2

Distribution of Danceability Data.

Chroma Features

Top song of 2020, SAULT - whywhywhywhywhy

Top song of 2020, SAULT - whywhywhywhywhy, Pitch

Timbre

Self similarity

Top song of 2021, Chaka Khan - I know you, I live you

Top song of 2021, Chaka Khan - I know you, I live you, Pitch

Timbre,

Self similarity,

Keys and chords

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Key name histogram

Key minor major

Tempo features

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An observation that I made is that the song with the highest tempo, can actually be viewed in halftime. It’s the song parachutes by Jordan Mackampa. The song is in my opinion in halftime so that would mean that it is not a 193 BPM but 97 BPM.


2020
# A tibble: 1 × 2
  minTempo maxTempo
     <dbl>    <dbl>
1     54.6     194.

2021
# A tibble: 1 × 2
  minTempo maxTempo
     <dbl>    <dbl>
1     66.0     180.

SD Tempo

SD tempo

Mean tempo

Key per song

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chordograms for my top songs, I know you, I live you

why why why why why